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The human immunodeficiency virus type 1 (HIV-1) integrase is an emerging target for novel antiviral drugs. Quantitative structure-activity relationship (QSAR) models for HIV-1 integrase inhibitors have been developed to understand the protein-ligand interactions to aid in the design of more effective analogs. This review paper presents a comprehensive overview of the computational modeling methods and results of QSAR models of HIV-1 integrase inhibitors published in 2005-2010. These QSAR models are classified according to the generation of molecular descriptors: 2D-QSAR, 3D-QSAR, and 4D-QSAR. Linear and non-linear modeling methods have been applied to derive these QSAR models, with the majority of the models derived from linear statistical methods such as multiple linear regression and partial least squares. While each of the published QSAR models have provided insights on the distinct chemical features of HIV-1 integrase inhibitors crucial for biological activity, only a few models have been used to propose and synthesize new HIV-1 integrase inhibitors. This study highlights the need for collaboration between computational and experimental chemists to utilize and improve these QSAR models to guide the design of the next generation of HIV-1 integrase inhibitors.
Department of Electrical and Computer Engineering, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-1309, USA. email@example.com.
This article was published in the following journal.
Name: Current computer-aided drug design
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Inhibitors of HIV INTEGRASE, an enzyme required for integration of viral DNA into cellular DNA.
Compounds which inhibit or antagonize biosynthesis or actions of integrase.
Enzyme of the HUMAN IMMUNODEFICIENCY VIRUS that is required to integrate viral DNA into cellular DNA in the nucleus of a host cell. HIV integrase is a DNA nucleotidyltransferase encoded by the pol gene.
A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories applicable to MOLECULAR BIOLOGY and areas of computer-based techniques for solving biological problems including manipulation of models and datasets.
Studies designed to examine associations, commonly, hypothesized causal relations. They are usually concerned with identifying or measuring the effects of risk factors or exposures. The common types of analytic study are CASE-CONTROL STUDIES; COHORT STUDIES; and CROSS-SECTIONAL STUDIES.
Human Immuno Deficiency Virus (HIV)
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Human Immunodeficiency Virus (HIV), the causative agent of AIDS. The Human Immunodeficiency Virus, more commonly known as HIV, is a member of the lentivirus sub-set of the retrovirus family of pathogens. It causes AIDS, or Acquired Immuno Deficiency Sy...